随着新能源的并网、电力电子设备的应用、负荷的多元化以及用户对电能质量要求的提高,配电网电能质量评估及治理越来越重要,传统的电能质量评估方法并不能很好的应用于愈发复杂的含高比例新能源配电网系统.针对这一问题,研究了一种基于序关系分析法(G1)与相关性定权法(Crite-ria Importance Though Intercrieria Correlation,CRITIC)的含高比例新能源配电网电能质量综合评判方法.首先,分析配电网中影响电能质量的因素,以及这些因素引起的电能质量问题,并依此提出配电网电能质量评价指标;接着利用G1法和CRITIC法确定主、客观权重,组合计算综合权重,并由模糊综合评判法进行配电网电能质量量化评估;最后,对所提方法进行实例验证.结果表明,该方法合理有效,对提升含高比例新能源配电网电能质量具有一定指导意义和参考价值.
Research on comprehensive evaluation method of power quality of distribution networks with high proportion of new energy based on G1 and CRITIC
With the grid connection of new energy,the application of power electronic equipment,the diversification of load and the im-provement of users'requirements for power quality,the power quality evaluation and governance of distribution network are becoming more and more important,while the traditional power quality evaluation methods can not be well applied to the increasingly complex dis-tribution network system with high proportion of new energy.Responding to this problem,a comprehensive evaluation method of distribu-tion network with high proportion of new energy power quality based on G1 method and Criteria Importance Though Intercrieria Correla-tion(CRITIC)was studied.Firstly,the factors affecting power quality in distribution network and the power quality problems caused by these factors were analyzed,and then the evaluation index of power quality in distribution network was proposed.Then G1 method and CRITIC method were used to determine the main and objective weights,combined to calculate the comprehensive weights,and the fuzzy comprehensive evaluation method was used to evaluate the power quality of distribution network quantitatively.Finally,the proposed method was validated by an example.The results show that the method is reasonable and effective,and has certain guiding significance and reference value for improving the power quality of the distribution network with high proportion of new energy.
distribution networkpower qualitycomprehensive weightfuzzy comprehensive evaluationquantitative assessment
万方数据
维普
